last update: 2019 12 14

Table of contents.

  1. Intelligence.
  2. Artificial intelligence (AI).
  3. Artificial general intelligence (AGI).
  4. Abstraction.
  5. Recent history of AI.


Intelligence is movement of things.

Useful intelligence and useful work is the same.

Even the most primitive machine is intelligent.



Physical awareness.

Artificial intelligence (AI).

Creation of AI by AI.

AI 1 (program, function) creates AI 2 (program, function) that creates good outputs for certain inputs.
AI 1 determines AI 2 by using many inputs that will resemble the expected inputs in the future.

The creation of AI by AI in a general way by the logic of trial and error and the judgement of outputs given certain inputs is a revolution in computer science.
This is not only passive machine programming but automated active machine learning by interaction with other forms of intelligence (human, AI).

Tactics of machine learning used commonly in 2019:

Use of AI by AI.

In a rather inefficient way, AI 2 could begin to use AI 1 randomly in order to optimize the use of AI 1 as part of the implementation of another AI.
After many iterations, AI 2 will learn about AI 1 and make good use of AI 1.
The use of AI 1 becomes part of the new AI function.

Humans started to learn about nature (science) in a random way.
Abstractions (aka knowledge, concepts, names, formulas, functions) are passed from persons to persons.

Will AI replace human programmers?

Only to some extent.

The programmer knows the problem and the wanted solution.
This is quite personal.

An AI can learn and predict a person better than the person itself.
Still, the person or programmer is the required input for the AI.

Will AI replace classic program languages and human made programs?

An AI learns from input (examples).
How to create the input?
This is why a program language is used.
The human programmer has already recognized patterns.
A pattern is declared as a type or function in the program language.
The transition or translation from input patterns to output patterns is declared as a function.

Artificial general intelligence (AGI).

My definition of AGI:
AGI means general logic and intelligence.
An AGI can judge the relations of received inputs.

The sooner AGI is created with free access to information, the better.
Any AI can become evil and/or insane with wrong or limited information.

An AI can be intelligent in arbitrary ways.

Useful intelligence means useful work.

Many AI have already surpassed the intelligence of the most intelligent humans in certain tasks.

A neural network is different from many other programs in that a neural network is programmed to do general logic by discovering and learning what limits what.
Like all programs, a neural network requires data in a certain structure.
But to compute logic to discover functions (limitations) in the given data of input and output (fact and consequence) is an ability of a neural network.
The data can represent anything and therefore the neural network does general logic.
E.g. logic to discover the traits (things) that indicate or enforce that a thing is a dog.

A human does AGI.

AGI does not mean great intelligence.

The common tactics of machine learning (deep learning, genetic programming) are sufficient and general enough to implement AGI.

IMO limitations of AI in 2019:


A computer system (e.g. a device or a brain) is limited regarding input and output and computed function from input to output.

Abstraction and reference are synonyms.
An abstraction of something is a reference to something.
Abstractions or references are utmost important for intelligence.
The notation of a reference is a real limiting thing or implementation.
The presentation on a paper. The perception by the eye or the hand of what is presented. The processing by the brain.

Fundamental theorem of software engineering.

Recent history of AI.

Convolutional Network Demo from 1993 (2014-06-02).

IBM Watson: Final Jeopardy! and the Future of Watson (2011-02-16).

The computer that mastered Go (2016-01-27).

DeepMind AI Reduces Google Data Centre Cooling Bill by 40% (2016-07-20).

AlphaGo Zero: Starting from scratch (2017-10-18).

A Chinese AI passed the national medical licensing exam, so technically it’s a doctor (2017-11-21).

Microsoft reaches a historic milestone, using AI to match human performance in translating news from Chinese to English (2018-03-14).
HN: Using AI to match human performance in translating news from Chinese to English ( (2018-03-15).

Google Duplex: A.I. Assistant Calls Local Businesses To Make Appointments (2018-05-08).

20 top lawyers were beaten by legal AI. Here are their surprising responses (2018-10-25).

Brain-to-Brain Communication is Coming! (2018-10-17).

This Curious AI Beats Many Games...and Gets Addicted to the TV (2018-11-17).

Building a Curious AI With Random Network Distillation (2018-12-02).

AlphaFold: Using AI for scientific discovery (2018-12-02).
AlphaFold @ CASP13: “What just happened?” (2018-12-09).
How one scientist coped when AI beat him at his life’s work (2019-02-15).
Inside DeepMind's epic mission to solve science's trickiest problem (2019-08-06).

This AI Learns From Humans…and Exceeds Them (2019-01-10).

DeepMind’s AlphaStar Beats Humans 10-0 (or 1) (2019-02-06).

New AI fake text generator may be too dangerous to release, say creators (2018-02-14).
AI can write just like me. Brace for the robot apocalypse (2019-02-15).

OpenAI Five Beats World Champion DOTA2 Team 2-0 (2019-05-18).
DeepMind Made a Math Test For Neural Networks (2019-06-04).
Article: Analysing Mathematical Reasoning Abilities of Neural Models (2019-04-02).

Capture the Flag: the emergence of complex cooperative agents (2019-05-30).
Video: Human-level in first-person multiplayer games with population-based deep RL (2018-07-06).

Aristo A.I. scores ‘A’ on 8th-grade science test (2019-09-04).
OpenAI’s GPT-2 Is Now Available - It Is Wise as a Scholar! (2019-10-01).

GLUE benchmark.
HN: Google T5 scores 88.9 on SuperGLUE Benchmark, approaching human baseline ( (2019-10-25).
r/singularity: Google T5 scores 88.9 on SuperGLUE Benchmark, compared to 89.8 human baseline (2019-10-25).